Challenge-response tests, such as a CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) are commonly used in computing to ensure that a request to perform an action on a computer system is not generated by a computer controlled process rather than a person. For example, a CAPTCHA may be used to determine whether a user requesting to post a comment to a message board is a person and not a computer controlled process for posting spam or other nefarious activities. A CAPTCHA typically includes a challenge that would be easy for a person to solve but would be difficult or extremely time consuming for a computer to solve. FIG. 1 illustrates a common type of CAPTCHA that displays a set of distorted letters and/or numbers to the user and requires that the user type the set of letters and numbers displayed. The letters and/or numbers are often significantly distorted to thwart the use of image analysis techniques that would enable a computer system to recognize the characters and/or numbers included in the CAPTCHA.
If the set of letters and numbers typed by the user matches the set of distorted letters and numbers, the user may be permitted to complete the action. If the user fails to correctly type the letters and/or numbers displayed in the CAPTCHA, the user is not permitted to complete the action. In some instances, the letters and/or numbers are so significantly distorted that a user may have a difficult time recognizing the characters and/or numbers represented. As a result, the user may have to make numerous attempts to decipher to distorted content, which may lead to user frustration. The problem of deciphering the distorted content may be compounded for users who have impaired vision or dyslexia.
Some attempts at replacements for a CAPTCHA as described in FIG. 1 are known. For example, U.S. Patent Application Publication No. 2009/0138723 to Nyang, et al. describes a CAPTCHA based on images, as opposed to text. Multiple images, such as photographs may be combined. Such combinations can include superimposing one image on top of another. The user is then asked to identify elements contained in the combined images. The combination of multiple images purportedly makes automated image analysis difficult.
Another contemplated replacement for a CAPTCHA as depicted in FIG. 1 is described in U.S. Patent Application Publication No. 2007/0201745 to Wang, et al. which describes another image based CAPTCHA. In the system described therein, multiple images are initially distorted. These images are then combined into a single composite image, but unlike Nyang, the images are not superimposed on each other, but rather are laid out in a non-overlapping manner. The borders of the multiple images are blurred to purportedly make image analysis difficult. A user identifies portions of the image that contain an element, and clicks on the element. The user must then annotate the element with a description of what it is.
Image based CAPTCHA tests as described in Nyang and Wang still suffer the same problems as the prior art CAPTCHA test depicted in FIG. 1. Superimposing and distorting images results in making it more difficult for a human to identify what is contained in the image. Furthermore, image analysis techniques are always improving. Superimposed images can be separated into their component parts. Blurred images can be un-blurred. Given enough time, image analysis techniques may be able to overcome any of the obfuscation methods described in Nyang and Wang.
These and other problems, are addressed by embodiments of the invention, individually and collectively.